Direction, evidence grade, and study type are AI-generated labels (gpt-5-mini), not human-verified. Syntheses are LLM-written. "Tensions" are machine-detected candidates, not confirmed contradictions. A research-acceleration tool, not peer review.
How this is built →
1Distinct papers
7Unique collaborators
0/1Semantic Scholar citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2444678977
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Ziqiong Zeng (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Innovation: 1 paper
- Productivity: 1 paper
Claim outcomes
- Other: 1 paper
- Task Completion Time: 1 paper
- Organizational Efficiency: 1 paper
- Output Quality: 1 paper
- Error Rate: 1 paper
- Training Effectiveness: 1 paper
Papers in the Semantic Scholar view
Latest stored Semantic Scholar author observations only. Citation counts below are from the same provider and are not combined with other services.
Scroll the table horizontally to see every column.
| Paper | Author evidence | Date | Provider citations |
|---|---|---|---|
| A decay-aware mixed-precision scheme slashes recurrent-state storage by about 69% and speeds up recurrent updates up to 2.01× while maintaining near-FP32 accuracy at 9.9 bits per state value, lowering end-to-end decoding cost (TPOT) by up to 10.9%.arxiv | Ziqiong Zeng provider id |
2026-08-27 | Missing, not zero |
Citation observation summary
Semantic Scholar supplied counts for 0 of 1 papers in this view; 1 are missing.